Using imprecise user knowledge to reduce redundancy in Association Rules
- https://doi.org/10.2991/ifsa-eusflat-15.2015.155How to use a DOI?
- Association Rules, Imprecise Knowledge, Knowledge Based Redundancy
Redundancy is a handicap in association rules. It becomes a limitation to use rules models in order to support the decision-making process. A technique based on user knowledge has been proposed recently, which aims at eliminating redundancy. However, it ignores the imprecise nature of knowledge. In this paper, the notion of knowledge redundancy is generalized and a method to propagate the user certainty over derivate rules is developed. Certainty factor models are used. Obtained results have shown a model reduction of 50% with previous knowledge below 3%. This method improves the efficiency of association rules and the use of discovered association rules.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Julio Diaz AU - Carlos Molina AU - M. Amparo Vila PY - 2015/06 DA - 2015/06 TI - Using imprecise user knowledge to reduce redundancy in Association Rules BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1098 EP - 1105 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.155 DO - https://doi.org/10.2991/ifsa-eusflat-15.2015.155 ID - Diaz2015/06 ER -